phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-12-12 04:00:42 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

more fixes

Browse source
This commit is contained in:
Ashwin Bharambe 2025-10-11 22:05:20 -07:00
parent bf59d26362
commit e5a1cdf554
9 changed files with 43 additions and 146 deletions
Download patch file Download diff file Expand all files Collapse all files

30
docs/static/deprecated-llama-stack-spec.html vendored
View file

@ -2623,17 +2623,7 @@
],
"summary": "Create a vector store file batch.",
"description": "Create a vector store file batch.\nGenerate an OpenAI-compatible vector store file batch for the given vector store.",
"parameters": [
{
"name": "vector_store_id",
"in": "path",
"description": "The ID of the vector store to create the file batch for.",
"required": true,
"schema": {
"type": "string"
}
}
],
"parameters": [],
"requestBody": {
"content": {
"application/json": {
@ -12154,19 +12144,6 @@
]
},
"description": "Set of key-value pairs that can be attached to the vector store"
},
"embedding_model": {
"type": "string",
"description": "(Optional) The embedding model to use for this vector store"
},
"embedding_dimension": {
"type": "integer",
"default": 384,
"description": "(Optional) The dimension of the embedding vectors (default: 384)"
},
"provider_id": {
"type": "string",
"description": "(Optional) The ID of the provider to use for this vector store"
}
},
"additionalProperties": false,
@ -12344,6 +12321,10 @@
"OpenAICreateVectorStoreFileBatchRequestWithExtraBody": {
"type": "object",
"properties": {
"vector_store_id": {
"type": "string",
"description": "The ID of the vector store to create the file batch for"
},
"file_ids": {
"type": "array",
"items": {
@ -12384,6 +12365,7 @@
},
"additionalProperties": false,
"required": [
"vector_store_id",
"file_ids"
],
"title": "OpenAICreateVectorStoreFileBatchRequestWithExtraBody",

27
docs/static/deprecated-llama-stack-spec.yaml vendored
View file

@ -1932,14 +1932,7 @@ paths:
Generate an OpenAI-compatible vector store file batch for the given vector
store.
parameters:
- name: vector_store_id
in: path
description: >-
The ID of the vector store to create the file batch for.
required: true
schema:
type: string
parameters: []
requestBody:
content:
application/json:
@ -9205,19 +9198,6 @@ components:
- type: object
description: >-
Set of key-value pairs that can be attached to the vector store
embedding_model:
type: string
description: >-
(Optional) The embedding model to use for this vector store
embedding_dimension:
type: integer
default: 384
description: >-
(Optional) The dimension of the embedding vectors (default: 384)
provider_id:
type: string
description: >-
(Optional) The ID of the provider to use for this vector store
additionalProperties: false
title: >-
OpenAICreateVectorStoreRequestWithExtraBody
@ -9346,6 +9326,10 @@ components:
"OpenAICreateVectorStoreFileBatchRequestWithExtraBody":
type: object
properties:
vector_store_id:
type: string
description: >-
The ID of the vector store to create the file batch for
file_ids:
type: array
items:
@ -9371,6 +9355,7 @@ components:
auto
additionalProperties: false
required:
- vector_store_id
- file_ids
title: >-
OpenAICreateVectorStoreFileBatchRequestWithExtraBody

30
docs/static/llama-stack-spec.html vendored
View file

@ -3357,17 +3357,7 @@
],
"summary": "Create a vector store file batch.",
"description": "Create a vector store file batch.\nGenerate an OpenAI-compatible vector store file batch for the given vector store.",
"parameters": [
{
"name": "vector_store_id",
"in": "path",
"description": "The ID of the vector store to create the file batch for.",
"required": true,
"schema": {
"type": "string"
}
}
],
"parameters": [],
"requestBody": {
"content": {
"application/json": {
@ -12680,19 +12670,6 @@
]
},
"description": "Set of key-value pairs that can be attached to the vector store"
},
"embedding_model": {
"type": "string",
"description": "(Optional) The embedding model to use for this vector store"
},
"embedding_dimension": {
"type": "integer",
"default": 384,
"description": "(Optional) The dimension of the embedding vectors (default: 384)"
},
"provider_id": {
"type": "string",
"description": "(Optional) The ID of the provider to use for this vector store"
}
},
"additionalProperties": false,
@ -12870,6 +12847,10 @@
"OpenAICreateVectorStoreFileBatchRequestWithExtraBody": {
"type": "object",
"properties": {
"vector_store_id": {
"type": "string",
"description": "The ID of the vector store to create the file batch for"
},
"file_ids": {
"type": "array",
"items": {
@ -12910,6 +12891,7 @@
},
"additionalProperties": false,
"required": [
"vector_store_id",
"file_ids"
],
"title": "OpenAICreateVectorStoreFileBatchRequestWithExtraBody",

27
docs/static/llama-stack-spec.yaml vendored
View file

@ -2553,14 +2553,7 @@ paths:
Generate an OpenAI-compatible vector store file batch for the given vector
store.
parameters:
- name: vector_store_id
in: path
description: >-
The ID of the vector store to create the file batch for.
required: true
schema:
type: string
parameters: []
requestBody:
content:
application/json:
@ -9670,19 +9663,6 @@ components:
- type: object
description: >-
Set of key-value pairs that can be attached to the vector store
embedding_model:
type: string
description: >-
(Optional) The embedding model to use for this vector store
embedding_dimension:
type: integer
default: 384
description: >-
(Optional) The dimension of the embedding vectors (default: 384)
provider_id:
type: string
description: >-
(Optional) The ID of the provider to use for this vector store
additionalProperties: false
title: >-
OpenAICreateVectorStoreRequestWithExtraBody
@ -9811,6 +9791,10 @@ components:
"OpenAICreateVectorStoreFileBatchRequestWithExtraBody":
type: object
properties:
vector_store_id:
type: string
description: >-
The ID of the vector store to create the file batch for
file_ids:
type: array
items:
@ -9836,6 +9820,7 @@ components:
auto
additionalProperties: false
required:
- vector_store_id
- file_ids
title: >-
OpenAICreateVectorStoreFileBatchRequestWithExtraBody

30
docs/static/stainless-llama-stack-spec.html vendored
View file

@ -3357,17 +3357,7 @@
],
"summary": "Create a vector store file batch.",
"description": "Create a vector store file batch.\nGenerate an OpenAI-compatible vector store file batch for the given vector store.",
"parameters": [
{
"name": "vector_store_id",
"in": "path",
"description": "The ID of the vector store to create the file batch for.",
"required": true,
"schema": {
"type": "string"
}
}
],
"parameters": [],
"requestBody": {
"content": {
"application/json": {
@ -14689,19 +14679,6 @@
]
},
"description": "Set of key-value pairs that can be attached to the vector store"
},
"embedding_model": {
"type": "string",
"description": "(Optional) The embedding model to use for this vector store"
},
"embedding_dimension": {
"type": "integer",
"default": 384,
"description": "(Optional) The dimension of the embedding vectors (default: 384)"
},
"provider_id": {
"type": "string",
"description": "(Optional) The ID of the provider to use for this vector store"
}
},
"additionalProperties": false,
@ -14879,6 +14856,10 @@
"OpenAICreateVectorStoreFileBatchRequestWithExtraBody": {
"type": "object",
"properties": {
"vector_store_id": {
"type": "string",
"description": "The ID of the vector store to create the file batch for"
},
"file_ids": {
"type": "array",
"items": {
@ -14919,6 +14900,7 @@
},
"additionalProperties": false,
"required": [
"vector_store_id",
"file_ids"
],
"title": "OpenAICreateVectorStoreFileBatchRequestWithExtraBody",

27
docs/static/stainless-llama-stack-spec.yaml vendored
View file

@ -2556,14 +2556,7 @@ paths:
Generate an OpenAI-compatible vector store file batch for the given vector
store.
parameters:
- name: vector_store_id
in: path
description: >-
The ID of the vector store to create the file batch for.
required: true
schema:
type: string
parameters: []
requestBody:
content:
application/json:
@ -11115,19 +11108,6 @@ components:
- type: object
description: >-
Set of key-value pairs that can be attached to the vector store
embedding_model:
type: string
description: >-
(Optional) The embedding model to use for this vector store
embedding_dimension:
type: integer
default: 384
description: >-
(Optional) The dimension of the embedding vectors (default: 384)
provider_id:
type: string
description: >-
(Optional) The ID of the provider to use for this vector store
additionalProperties: false
title: >-
OpenAICreateVectorStoreRequestWithExtraBody
@ -11256,6 +11236,10 @@ components:
"OpenAICreateVectorStoreFileBatchRequestWithExtraBody":
type: object
properties:
vector_store_id:
type: string
description: >-
The ID of the vector store to create the file batch for
file_ids:
type: array
items:
@ -11281,6 +11265,7 @@ components:
auto
additionalProperties: false
required:
- vector_store_id
- file_ids
title: >-
OpenAICreateVectorStoreFileBatchRequestWithExtraBody

4
llama_stack/apis/vector_io/vector_io.py
View file

@ -491,11 +491,13 @@ class OpenAICreateVectorStoreRequestWithExtraBody(BaseModel, extra="allow"):
class OpenAICreateVectorStoreFileBatchRequestWithExtraBody(BaseModel, extra="allow"):
"""Request to create a vector store file batch with extra_body support.
:param vector_store_id: The ID of the vector store to create the file batch for
:param file_ids: A list of File IDs that the vector store should use
:param attributes: (Optional) Key-value attributes to store with the files
:param chunking_strategy: (Optional) The chunking strategy used to chunk the file(s). Defaults to auto
"""
vector_store_id: str
file_ids: list[str]
attributes: dict[str, Any] | None = None
chunking_strategy: VectorStoreChunkingStrategy | None = None
@ -847,13 +849,11 @@ class VectorIO(Protocol):
)
async def openai_create_vector_store_file_batch(
self,
vector_store_id: str,
params: Annotated[OpenAICreateVectorStoreFileBatchRequestWithExtraBody, Body(...)],
) -> VectorStoreFileBatchObject:
"""Create a vector store file batch.
Generate an OpenAI-compatible vector store file batch for the given vector store.
:param vector_store_id: The ID of the vector store to create the file batch for.
:returns: A VectorStoreFileBatchObject representing the created file batch.
"""
...

12
llama_stack/core/routers/vector_io.py
View file

@ -135,7 +135,7 @@ class VectorIORouter(VectorIO):
logger.debug(f"VectorIORouter.openai_create_vector_store: name={params.name}, provider_id={provider_id}")
# If no embedding model is provided, use the first available one
# TODO: this branch will soon be deleted so you _must_ provide the embedding_model when
# TODO: this branch will soon be deleted so you _must_ provide the embedding_model when
# creating a vector store
if embedding_model is None:
embedding_model_info = await self._get_first_embedding_model()
@ -383,17 +383,13 @@ class VectorIORouter(VectorIO):
async def openai_create_vector_store_file_batch(
self,
vector_store_id: str,
params: Annotated[OpenAICreateVectorStoreFileBatchRequestWithExtraBody, Body(...)],
) -> VectorStoreFileBatchObject:
logger.debug(
f"VectorIORouter.openai_create_vector_store_file_batch: {vector_store_id}, {len(params.file_ids)} files"
)
provider = await self.routing_table.get_provider_impl(vector_store_id)
return await provider.openai_create_vector_store_file_batch(
vector_store_id=vector_store_id,
params=params,
f"VectorIORouter.openai_create_vector_store_file_batch: {params.vector_store_id}, {len(params.file_ids)} files"
)
provider = await self.routing_table.get_provider_impl(params.vector_store_id)
return await provider.openai_create_vector_store_file_batch(params)
async def openai_retrieve_vector_store_file_batch(
self,

2
llama_stack/providers/utils/memory/openai_vector_store_mixin.py
View file

@ -978,10 +978,10 @@ class OpenAIVectorStoreMixin(ABC):
async def openai_create_vector_store_file_batch(
self,
vector_store_id: str,
params: Annotated[OpenAICreateVectorStoreFileBatchRequestWithExtraBody, Body(...)],
) -> VectorStoreFileBatchObject:
"""Create a vector store file batch."""
vector_store_id = params.vector_store_id
if vector_store_id not in self.openai_vector_stores:
raise VectorStoreNotFoundError(vector_store_id)